Abstract
This paper features an analysis of the relative effectiveness, in terms of the Adjusted R-Square, of a variety of methods of modelling realized volatility (RV), namely the use of Gegenbauer processes in Auto-Regressive Moving Average format, GARMA, as opposed to Heterogenous Auto-Regressive HAR models and simple rules of thumb. The analysis is applied to two data sets that feature the RV of the S&P500 index, as sampled at 5 min intervals, provided by the OxfordMan RV database. The GARMA model does perform slightly better than the HAR model, but both models are matched by a simple rule of thumb regression model based on the application of lags of squared, cubed and quartic, demeaned daily returns.
Keywords
GARMA, Gegenbauer processes, HAR models, realized volatility, rules of thumb
Document Type
Journal Article
Date of Publication
10-1-2023
Volume
11
Issue
10
Publication Title
Risks
Publisher
MDPI
School
School of Business and Law
RAS ID
64619
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
Allen, D. E., & Peiris, S. (2023). GARMA, HAR and rules of thumb for modelling realized volatility. Risks, 11(10), article 179. https://doi.org/10.3390/risks11100179